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Open nowPosted 2600 days ago

硬件加速推理AI Infra工程师(AI芯片) - 芯片研发

ByteDance19,208 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now硬件加速推理AI Infra工程师(AI芯片) - 芯片研发ByteDance · Beijing, Chinese Mainland
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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 2 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 2600 days ago

ByteDance median: 2 days open

The posting

团队介绍:AI芯片团队深耕人工智能芯片研发领域,产品覆盖云端与终端场景,致力于提供高效率、低成本的AI芯片及 SoC 解决方案,满足公司内外AI及相关业务的算力需求。团队自主设计了多款AI芯片,涵盖推理、训练场景,具有高性能、高精度、高灵活性、编译器友好、低成本等特点。核心AI加速核与AI软件栈均为自主研发,具备完整知识产权,能够支撑面向不同模型、不同部署场景的持续演进与优化。

1、负责大模型等业务模型在自研芯片进行适配性和性能评估、软硬件协同优化工作; 2、负责AI模型整图或者算子编译框架优化,实现较高硬件利用率和整体性能,提升编译框架的通用性与优化能力; 3、构建分布式推理系统,推理框架极致调优,实现较优的在线部署吞吐和高性价比; 4、模型量化、稀疏、蒸馏等推理部署的探索和落地方案。

1、深入理解AI加速硬件的体系结构和并行计算; 2、熟悉深度学习框架和软件栈,熟练使用C/C++、Python等编程语言; 3、熟悉ONNX/TensorFlow/PyTorch等主流深度学习框架; 4、有主动学习、问题分析与解决能力和较强自驱力;具备良好的跨团队协作能力。

以下为加分项: 1、熟悉编译器和代码优化技术,有MLIR、TVM等相关开发经验; 2、熟悉GPU或者主流AI芯片架构,有相关算子优化、图编译优化经验、硬件评测经验; 3、对LLM或多模态领域模型有深刻理解,例如Qwen、Deepseek等; 4、有AI加速硬件的量化工具开发经验; 5、熟悉AI服务器和集群架构,熟悉芯片和集群互联相关技术,有实践开发经验; 6、有vLLM/SGLang等推理框架开发和调优经验,有部署实践相关经验。

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